Use Cases
Privacy-Preserving AI Across Industries
From ecommerce to healthcare, Tenzro enables AI applications that respect privacy, ensure compliance, and improve continuously through collaborative learning.
Ecommerce
Personalized recommendations without tracking individuals
AI recommendation engine runs entirely in the customer's browser. It analyzes browsing patterns, purchase history, and interactions locally - never sending data to servers. Each customer's browser trains a local model copy, then contributes encrypted updates to improve the global model through federated learning. Merchants receive aggregate insights about trends and preferences without ever accessing individual customer data. The platform creates a data flywheel: more shoppers generate better recommendations, attracting more customers, which further improves the model - all while maintaining complete privacy.
Key Features
- •Browser-based recommendation engine with WebGPU acceleration
- •Real-time personalization from local behavior analysis
- •Privacy-preserved collaborative training across all shoppers
- •Aggregate merchant insights without individual data access
- •Autonomous improvement through continuous learning
- •No cookies, tracking pixels, or PII storage required
- •Works offline for returning customers
- •Dynamic pricing optimization from aggregate patterns
Benefits
- •GDPR and privacy regulation compliant by design
- •Better recommendations improve over time automatically
- •Zero liability from storing customer data
- •Reduced infrastructure and compliance costs
- •Increased customer trust and conversion rates
- •Competitive advantage through continuous improvement
Healthcare
Diagnostic models trained across hospitals without sharing patient data
Each hospital trains locally, submits encrypted updates. Global model improves while maintaining HIPAA compliance. Hospitals collaborate on AI while keeping patient data completely private.
Key Features
- •Local training on patient data
- •Encrypted gradient sharing
- •Global model improvement
- •HIPAA compliant architecture
- •Cross-institution collaboration
- •Privacy-preserved research
Benefits
- •Better diagnostic accuracy
- •Regulatory compliance
- •Protected patient privacy
- •Collaborative medical research
Finance
Fraud detection models that run in TEEs without exposing transactions
Banks contribute to shared intelligence while protecting proprietary data and customer information. Fraud detection improves across the network without revealing transaction details.
Key Features
- •TEE-secured model execution
- •Encrypted transaction processing
- •Shared fraud intelligence
- •Protected customer data
- •Real-time detection
- •Cross-bank collaboration
Benefits
- •Improved fraud detection
- •Protected proprietary data
- •Regulatory compliance
- •Network effect benefits
SaaS Applications
AI copilots that process documents locally
Users get assistance without sending content to servers. Company avoids liability of storing sensitive documents. Perfect for legal, financial, and enterprise document processing.
Key Features
- •Client-side document processing
- •Local AI assistance
- •No server uploads
- •Offline capability
- •Zero data liability
- •Enterprise security
Benefits
- •No storage liability
- •Customer trust
- •Compliance friendly
- •Reduced infrastructure costs
Enterprise AI Platforms
Build complete AI platforms with custom ecosystems
Framework for building platforms with orchestration, agents, MCPs, knowledge bases, and RAG. Create self-improving systems through autonomous training loops and data flywheels.
Key Features
- •Multi-model orchestration
- •Agent-based systems
- •MCP integration
- •RAG/DAG workflows
- •Autonomous improvement
- •Custom ecosystem building
Benefits
- •Complete platform control
- •Continuous improvement
- •Competitive moat
- •Reduced development time
Common Patterns Across Use Cases
Local Execution
Data stays on device, processed locally without transmission
Collaborative Learning
Models improve through federated training without data sharing
Privacy Compliance
Built-in compliance with GDPR, HIPAA, and other regulations
Build Your Privacy-First Application
Start building AI applications that respect privacy and comply with regulations